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Comparison of multi-cancer early detection with LDCT in a lung cancer screening population

Principal Investigator
Name
Jonathan Heiss
Degrees
Ph.D.
Institution
GRAIL, LLC
Position Title
Bioinformatics Scientist 2
Email
About this CDAS Project
Study
NLST (Learn more about this study)
Project ID
NLST-1014
Initial CDAS Request Approval
Feb 8, 2023
Title
Comparison of multi-cancer early detection with LDCT in a lung cancer screening population
Summary
The USPSTF currently recommends low-dose computed tomography (LDCT) for lung cancer screening, though only for individuals at high risk. GRAIL has developed multi-cancer early detection (MCED) technology and enrolled patients from both low and high risk populations in several clinical trials including CCGA (NCT02889978), PATHFINDER (NCT04241796) and SUMMIT (NCT03934866). Differences in the targeted screening populations complicate the comparison of the performance of these two screening modalities. We propose to match participants of the listed GRAIL studies with NLST participants to facilitate a better comparison, and secondly, to provide insight into the performance of MCED to detect a broad range of cancers in a high risk population.
Aims

* Compare sensitivity and specificity of LDCT and GRAIL's MCED technology for detection of lung cancer across NLST and CCGA/PATHFINDER/SUMMIT study populations, controlling for cancer stage, size, and subtype and common demographic differences such as age, sex, smoking history, and self-reported ethnicity. Perform matching using generalized overlap weights [1], which are reported to have improved balancing properties compared to inverse propensity score weights.
* Estimate detection rate of non-lung cancers using GRAIL’s MCED technology in the high-risk NLST study population

[1] Li F, Thomas LE, Li F. Addressing extreme propensity scores via the overlap weights. American Journal of Epidemiology. 2019 Jan 1;188(1):250-7

Collaborators

John Beausang, GRAIL
Joerg Bredno, GRAIL
Geoff Stanley, GRAIL
Ellen Chang, GRAIL
Christina Clarke, GRAIL
Earl Hubbell, GRAIL
Zhaoyu Yin, GRAIL
Rita Lopatin, GRAIL
James Dai, GRAIL
Xinyi Hou, GRAIL
Bong Chul Chu, GRAIL